Comparative Studies | Computer Science & Engineering | India | Volume 6 Issue 2, February 2017
A Comparative Study of Algorithms used for Detection and Classification of Plant Diseases
Roshni C.R, Dr. M. Safish Mary
Our Countrys economy prospect lies mainly in agricultural sector. Although there is much advancement in technology, still chances of predicting the diseases in plants are vague. In this paper, a technical solution for the farmers to detect and diagnose the right disease affecting the plants is discussed. The Content Based Image Retrieval (CBIR) technique is used to retrieve the images of diseased plant from the training dataset based on a query image. The images thus retrieved are segmented using Hierarchical Clustering which produces cluster of diseased plant images. The clusters are then classified using Support Vector Machine (SVM) classifier based on the features extracted from clusters which verifies correct type of disease affecting the plant set.
Keywords: CBIR, Hierarchical Clustering, Segmentation, Feature Extraction, SVM
Edition: Volume 6 Issue 2, February 2017
Pages: 2147 - 2150
How to Cite this Article?
Roshni C.R, Dr. M. Safish Mary, "A Comparative Study of Algorithms used for Detection and Classification of Plant Diseases", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20171105, Volume 6 Issue 2, February 2017, 2147 - 2150
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